Work

A master-sub algorithm fusion strategy for full-coverage path planning of deep-sea mining vehicle clusters

Year: 2025

Type: article

Abstract: In deep-sea mining, effective path planning for vehicle clusters is crucial. Notably, few existing path-planning studies consider pipeline-related factors. This paper presents a master-sub algorithm fusion strategy for the full-coverage path planning of deep-sea mining vehicle clusters in a pipe-lifting system. The master-algorithm uses an improved DDQN algorithm to cover mining areas efficiently and avoid hose entanglement. The sub-algorithm combines a modified inner-spiral algorithm with an A * algorithm for wide-area coverage. Experiments show this strategy achieves 100% coverage in complex environments, prevents hose entanglement, and enables vehicle and hose recovery.

Source: International Journal of Naval Architecture and Ocean Engineering

DOI: 10.1016/j.ijnaoe.2025.100673

Authors: Bowen Xing, Hanzheng Chen, Zhenchong Liu, Xiao Wang, Chuanxu Yan

Institution: Shanghai Ocean University

Language: English

Topic: Robotic Path Planning Algorithms

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $1,200